385.19平米二層山莊別墅工程量計(jì)算書及清單計(jì)價(jià)含建筑結(jié)構(gòu)圖外文翻譯

1、（論文外文翻（2009題目：EstimatingFutureHighwayConstruction2009 2 月 19EstimatingFutureHighwayConstructionC.G.Wilmot,M.ASCE,1andG.Cheng,Abstract: The objective of this research was to develop a model that estimates future highway construction costs in Louisiana. The model describes overall highway construction

2、 cost in terms of a highway construction cost index. The index is a composite measure of the cost of construction labor, materials, and equipment; the characteristics of contracts; and the environment in which contracts are let. Future construction costs are described in terms of predicted index val

3、ues based on forecasts of the price of construction labor, materials, and equipment and the expected contract characteristics and contract environments. The contract characteristics and contract environments that are under the control of highway agency officials, can be manipulated to reflect future

4、 cost-cutting policies. Application of the model in forecasting to highway construction costs in Louisiana shows that the model closely replicates past construction costs for the period 19841997. When applied to forecasting future highway construction costs, the model predicts that highway construct

5、ion costs in Louisiana will double between 1998 and 2015. Applying cost-cutting policies and assuming input costs are 20% less than anticipated, the model estimates highway construction costs will increase by 75% between 1998 and 2015.Keywords:Highwayconstruction;Costs;State Departments of Transport

6、ation are required to prepare highway construction programs that describe their planned construction activity in the short term. There is usually considerable interest inthe programfrom local authorities, politicians, and interest groups. Draft programs are typically presented to the public and to v

7、arious agencies at the local, regional, state, and federal level for comment and review. Ultimately, a program will be approved by the state legislature and will become the formal program of construction of the state Department of Transportation until a new program is developed in the next cycle a f

8、ew years later.Becauseindividualprojectsare ofconsiderable importance to politiciansandindividual interest groups, it is common thatprogresson a construction programis closely monitored. Any deviation islikely to be queried, and the Secretary of the state Department of Transportation or a senior off

9、icial in the department will often have to defend the situation publicly or in the state legislature. This can lead to perceptions of incompetence and erosion of support from the legislature and the public.To prepare reliable highway construction programs, road authorities must have accurate estimat

10、es of future funding and project costs. While future funding isobviously never known witha great deal of certainty, it is often the estimation of project costs that cause upsets in the execution of construction programs. Inaccurate cost estimation is one source of error, but another, the escalation

11、in cost of a project over time, is another source disruption to the program that is usually not anticipated and catered for. Typically, whenprojects are costed, their costs are estimated in terms of the current cost of the project, and this estimate is not adjusted for the year in which the project

12、is scheduled for implementation. These cost increases can be significantand are, of course, cumulative acrossprojects;also, they rise atan increasing rate each year into the future. Estimating future highway construction is the focus of this paper. The model developed in this study was developed wit

13、h data from the Louisiana Department of Transportation and Development DOTD! and is therefore particular to that state. However, the methodology employed could be employed in other areas.MeasuringProjectWhen construction in the field lags behind planned construction in the construction program, it i

14、s usually because the projects that have been constructed have cost more than anticipated. This is not random variation of actual costs about estimated costs, because, clearly, underestimates would cancel out overestimates over time in such a situation. Rather, it is evidence of a consistent underes

15、timateof all projects collectively. The benefit of this is that it can be measured at the overall level, which is much easier to measure than at the individual project level.In the past, change in overall construction costs has been measured in terms of construction indices. These indices are weight

16、edaverages of the cost of a set of representative pay items over time. They have been used to display cost trends in the past. However, there is no reason why cost indices must be restricted to displaying past trends; they can also portray future overall costs, provided the representative pay items

17、on which the index is based can be forecast. A predictive construction cost index was adopted in this study to describe the change in overall construction costs in the future. The formulation of the index is described later in the paper.PastIncreasesinConstructionWhen the change in overall construct

18、ion costs in the past is observed（as measured by popular construction cost indices）, it is apparent that theychange significantly from year to year and that the changes can sometimes be quite erratic. The common assumption that construction costs change with the rate of inflation can lead to poor es

19、timates of future construction cost. To illustrate, the Federal HighwayAdministrations Composite Bid Price Index, an index of overall highway construction costs, is plotted in Fig. 1 together with the Consumer Price Index （CPI）, a common expression of general inflation. The FHWA CBPI for the entire

20、nation and for Louisiana alone is plotted in the diagram. All indices have been normalized to a value of 100 in 1987 for comparison purposes. From the diagram, it is clear that highway construction costs change erratically and even display different short and long-term trends from to those of the CP

21、I. It is also apparent that construction cost changes are different in Louisiana from those in the nation as a While not shown here, review of the FHWA CBPI from other states shows that many of them show a deviation from national values.PastMethodsofForecastingHighwayConstructionForecastingfuture hi

22、ghway constructioncostshas beenachieved inbasicallythreewaysin the past. unit rates of construction such as dollars per mile by highway type have been used to estimate construction costs in the short term. However, this method has generally been found to be unreliable, because site conditions such a

23、s topography, in situ soil, land prices, environment, and traffic loads vary sufficiently from location to location to make average prices inaccurate estimates of the price of individual projects or even of all projects in a particular year.Second, extrapolation of past trends, or time-series analys

24、is, has been used to forecast future overall constructioncosts （Koppula1981;Hartgenetal.1997）.Typically,constructioncostshavebeencollapsedin these analyses to a single overall expression of constructioncost such as the FHWA CBPI or the Engineering News Records Building Construction Index ENR BCI! or

25、 Construction Cost Index ENR CCI!. However, these types of models are usually only used for short-term forecasting due to their reliance on the notion that past conditions are maintained in the future.Third, models have been established that describe construction costs as a function of factors belie

26、ved to influence construction costs. The relationship between construction costs and these factors have been establishedfrompastrecordsofconstructioncosts. Typically, the modelsestablished inthis mannerhave been used to estimate the cost of individual contracts. These models, with their relational s

27、tructure, are the only models expected to provide reliable long-term estimates. The model developed in this study is of this type.ProposedConstructionCostIt is clear that there are numerous factors that affect construction costs. However, it is striking that most construction cost models developed i

28、n the past have used only a few of the many influential factors identified above. One reason for this is that information is generally not available on many factors in data sets used to estimate models. Another reason is that information on the qualitative conditions surrounding each contract is dif

29、ficult to obtain. These are problems that prevail in most circumstances and are difficult to overcome.Tomitigateagainstthe effectofanincomplete setoffactors,twostrategiescanbe employed.First,itmay be possible to represent some of the absent factors by surrogate variables that are in the data set. Fo

30、r example, as mentioned earlier, annual bid volume has been used in the past as an inverse measure of the level of competition prevailing in the construction industryat thattime （Herbsman 1986）.Similarly, the number of plan changes each year can serve as a measure of design quality. Second, if the m

31、odeling of construction cost is changed from estimating the cost of individual projects to estimating overall construction costs each year, the modeling task is simplified. This is because it is no longer necessary to try to model individual projects in which conditions inflate the price in one case

32、 and deflate it in another, since such conditions would tend tocancel themselves out among projects in the same year. For example, firms that reduce their bid prices in an effort towina particular contract could be balancedoutwithin the same fiscal year bythose that increase their prices because the

33、y already have enough work and are not particularly interested in winning the contract. Similarly, those firms with expertise in the type of construction required will be balanced out by those with low levels of expertise in that area. Thus, it is generally more tolerable to operate with fewer relev

34、ant factors when modeling at the aggregate or overall level than when modeling at the disaggregate level.The objective of this study is to establish a model, estimated on historical quantitative data, that incorporates as many relevant variables as possible and is capable of estimating the future ov

35、erall cost of highway construction on an annual basis. The model is intended to assess the impact of alternative future conditions on highway construction costs and assist officials of the Louisiana DOTD to identify management policies that will help limit the increase in highway construction costs

36、in the state.It was also the perception of those interviewed that contracts let in the fourth quarter of the fiscal year tended to result in higher bid prices. This was because there was a tendency for projects to accumulate in the fourth quarter due to various delays, and the increased volume of pr

37、ojects resulted in decreased competition among contractors.ModelThe model developed to predict overall highway construction costs in this study is based on five submodels of price estimation. Each submodel estimates the price of a pay item representative of cost model a dominant construction area. D

38、ominant construction areas were identified from past expenditure in different areas of highway construction. From the Louisiana DOTD data for the period19841997, it was found that more than 50% of all highway construction expenditure occurred in the areas of asphalt concrete surfaces, Portland cemen

39、t concrete surfaces, excavation and embankment, structural steel, structural concrete, and reinforcingsteel.Interestingly,theseconstructionareasareidenticaltothoseusedtoestimatetheFHWACBPI. The structural steel constructionareawas notincluded in the model developed in this study, because more than 9

40、8% of expenditure in this construction area was bid as a lump sum in each contract with no record of the amount of steel included in the bid. This made comparison of the cost of structural steel among contracts impossible. The other five construction areas included in the model were all represented

41、by pay items whose prices were expressed in terms of rates, which permitted comparison among contracts.A schematic representation of the overall model with its five submodels is shown in Fig. 2. Each submodel estimates the price of a representative pay item from each of the five dominant constructio

42、n areas. The contribution of each submodel to the overall model is accomplished by combining the prices of the representative payitemsinanindexsimilar tothatof theFHWA CBPI.Inthiscase,because the formulationis slightly different from the FHWA CBPI and is constructed specifically to reflect past and

43、future overall construction costs in Louisiana, it is named the Louisiana Highway Construction Index and is defined asModelperformance is ideallyvalidatedusing data notused inthe estimation of the model. Inthiscase such data was available. Dividing the existing data set into two portions to estimate

44、 the model on one portion and use the other for validation was not practical, given the limited sample size in some of the submodels. For example, the concrete pavement submodel has a total of only 212 observations, and estimating the submodel on the highly variable data on fewer observations would

45、reduce the accuracy of the estimates. Thus, the performance of the model was assessed by observing how well it reproduced observed construction costs.Using the same data as that on which the model was calibrated, the estimated and observed LHCI values for the period 19841997 are shown in Fig. 3. The

46、 95% confidence limit of the observed LHCI is also shown in the figure to illustrate that the estimated LHCI values are, for the most part, contained within the 95% confidence limit of the observed LHCI values. The chisquared test of the similarity of the estimated and observed LHCI values indicates

47、 that a significant difference could not be observed at the 99% level of Investigating the behavior of the construction cost index in Fig. 3 reveals interesting reasons behind the observed behavior. Reviewing the data and observing its impact on the forecasts through the model allows an analyst to d

48、etermine the primary causes of change in construction costs during certain periods in the past. For example, the main cause of the decrease in construction costs observed in the period 19841986 can be traced back to a decline in labor and petroleumcosts during thatperiod. The rapid increase in const

49、ruction costsfrom 1995 to 1996 was primarily due to a combination of rising petroleum costs and an increased proportion of smaller contracts. The drop inconstructioncosts observed immediately following thisevent(i.e.,in 1997) was mainly the consequence of an increase in the average size of projectsf

50、rom those let in 1996, veryfew projects being let in the fourth quarter, and a decrease in the average duration of projects.This study has shown that the literature indicates that a comprehensive set of factors contributes to the cost of highway construction. In this study, the most influential fact

51、ors were found to be the cost of the material, labor, and equipment used in constructing the facility. However, characteristics of individual contracts and the contracting environmentin which contracts are letalso affectconstruction costs. In particular, contract size, duration, location, and the qu

52、arter in which the contract is let were found to have a significant impact on contract cost. Bid volume, bid volume variance, number of plan changes, and changes in construction practice, standards, or specifications also make a significant impact on contract costs. Other factors are expected to hav

53、e an impact on construction costs but were not included in this analysis because no data on their values were available.The model developed in this study reproduces past overall construction costs reasonably accurately at the aggregate level. Predicted overall construction costs are not significantl

54、y different from observed costs at the 99% level of significance. This accuracy is largely the result of the aggregate levelat which construction costs are measuredin thisstudy;at the individualcontractlevel, the submodels capture only between 42and 72% of the variation in the data. It is suspected

55、that much of this variation is due to unobserved, essentially subjective factors that influence the bid prices in individual contracts. However, some of these idiosyncratic variations attheindividualcontractlevelaverageoutintheaggregationThis model can be used by highway officials in Louisiana to te

56、st alternative contract management strategies. Increasing contract sizes, reducing the duration of contracts, reducing bid volume and bid volume variance, reducing the number of plan changes, and reducing the proportion of contracts let in the fourth quarter allserve toreduce overallconstructioncost

57、s.Highwayofficialscanassessthe impactof strategiesthey believe are achievable by applying the model. Most importantly, though, the model can assist in estimating future construction costs and providing the means to produce more reliable construction programs.Associate Professor, Louisiana Transporta

58、tion Research Center and Dept. of Civil and Environmental Engineering, Louisiana State Univ., Baton Rouge, LA 70803-6405.CivilEngineer,GEC,Inc.,9357InterlineAve.,BatonRouge,LAC.G.Wilmot,M.ASCE,andG.Cheng,P.EEstimatingFutureHighwayConstructionCostsJOURNALOF CONSTRUCTION ENGINEERING AND MANAGEMENT ASC

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